The role of Machine Learning (ML) in imaging is becoming increasingly prominent. Benefiting from the generation of ever-larger datasets, incorporating ML into imaging paradigms is full of promises: enabling better reconstructions and easier quantitative analysis; performing faster and higher-resolution imaging; maintaining image quality while taking fewer measurements; using imaging data for personalized applications; and so on.

In this track, we'll discuss the key ML trends emerging in various imaging fields, from computer vision to medical imaging or autonomous driving --- and many others. Through a series of high-level thematic talks, our aim is to highlight the principal challenges and opportunities ahead for ML in imaging.